Aqua MODIS gross primary productivity (GPP) data from the MYD17A2HGF product over Central America from December 26 - 31, 2020.View full-size image
The MYD17A2HGF Version 6.1 Gross Primary Productivity (GPP) Gap-Filled product is a cumulative 8-day composite of values with 500 meter (m) pixel size based on the radiation use efficiency concept that can be potentially used as inputs to data models to calculate terrestrial energy, carbon, water cycle processes, and biogeochemistry of vegetation. The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data product includes information about GPP and Net Photosynthesis (PSN). The PSN band values are the GPP less the Maintenance Respiration (MR). The data product also contains a PSN Quality Control (QC) layer. The quality layer contains quality information for both the GPP and the PSN.
The MYD17A2HGF will be generated at the end of each year when the entire yearly 8-day MYD15A2H is available. Hence, the gap-filled MYD17A2HGF is the improved MYD17, which has cleaned the poor-quality inputs from 8-day Leaf Area Index and Fraction of Photosynthetically Active Radiation (LAI/FPAR) based on the Quality Control (QC) label for every pixel. If any LAI/FPAR pixel did not meet the quality screening criteria, its value is determined through linear interpolation. However, users cannot get MYD17A2HGF in near-real time because it will be generated only at the end of a given year.
|File Size||~10 MB|
|Temporal Extent||2002-01-01 to Present|
|Geographic Dimensions||1200 km x 1200 km|
|Number of Science Dataset (SDS) Layers||3|
|Columns/Rows||2400 x 2400|
|Pixel Size||500 m|
|SDS Name||Description||Units||Data Type||Fill Value||No Data Value||Valid Range||Scale Factor|
|Gpp_500m||Gross Primary Productivity||kgC/m²/8day||16-bit signed integer||32761 to 32767||N/A||0 to 30000||0.0001|
|PsnNet_500m||Net Photosynthesis||kgC/m²/8day||16-bit signed integer||32761 to 32767||N/A||-30000 to 30000||0.0001|
|Psn_QC_500m||Quality Control Indicators||Bit Field||8-bit unsigned integer||255||N/A||0 to 254||N/A|
|32761||Land cover assigned as "unclassified" or not able to determine|
|32762||Land cover assigned as urban/built-up|
|32763||Land cover assigned as "permanent" wetlands/inundated marshland|
|32764||Land cover assigned as perennial snow, ice|
|32765||Land cover assigned as barren, sparse veg (rock, tundra, desert)|
|32766||Land cover assigned as perennial salt or inland fresh water|
For the year-end gap-filled MYD17A2HGF, users may ignore the QC data layer because cloud-contaminated LAI/FPAR gaps have been temporally filled prior to calculation.
Mappings for the Psn_QC_500m layer and an explanation of how to interpret this information are provided under Section 4.1 in the User Guide.
The quality layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret this layer.
Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.
In addition to data access and transformation processes, AppEEARS also has the capability to unpack and interpret the quality layers.